{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jp18390\Dropbox\DISCRIMINATION PROJECT (U.S. FEDERAL AGENCIES)\Age Discrimination Project\PAR R&R\Statistics\Age_Discrimination.APPENDIX 1.MISC SENSITIVITY CHECKS.06-02-2022.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 2 Jun 2022, 18:05:42
{txt}
{com}.    
.    
. 
. use "C:\Users\jp18390\Dropbox\DISCRIMINATION PROJECT (U.S. FEDERAL AGENCIES)\Age Discrimination Project\PAR R&R\Statistics\Age_Discrimination.Post-Estimation.06-02-2022.dta", replace 
{txt}
{com}. 
. 
. 
. 
. **** 2022 PAR Data Replication [06/02/2022]: "STATUS-GROUP POWER DIFFERENTIALS AND AGE DISCRIMINATION WITHIN THE U.S. FEDERAL WORKFORCE" [KRAUSE & PARK] ****
. 
.  
.  
. **** APPENDIX SECTION 1: MISCELLANEOUS SENSITIVITY CHECKS *****
.  
.  
.  
.  
. ***  APPENDIX SECTION 1A: MODEL SPECIFICATIONS CONTROLLING FOR ONE-YEAR LEAD OF ORGANIZATIONAL JUSTICE COVARIATE [CONCERN: SIMULATANEITY BIAS OF THIS CONTROL COVARIATE WITH AGE DISCRIMINATION FORMAL COMPLAINTS MAY INADVERTENTLY BIAS THE MAIN COVARIATES OF INTEREST] **** 
. 
. 
. ***  APPENDIX SECTION 1B: MODEL SPECIFICATIONS DROPPING VETERANS AFFAIRS; DROPPING EXTREME CASES OF THE MAIN COVARIATES & DEPENDENT VARIABLE **** 
. 
.    
.    
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
.    
. 
. 
. xtset a_id year, yearly
{res}{txt}{col 8}panel variable:  {res}a_id (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2010 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 year
{txt}
{com}. 
. *
. *   
. *
. 
. 
. ** Create One-Year Ahead 'Lead' of Organizational Justice Covariate **
. 
. gen f1_orgjustice_sem = f1.orgjustice_sem
{txt}(179 missing values generated)

{com}. 
. 
. 
. 
. *** TABLE A1.1: APPENDIX SECTION 1A REGRESSION MODEL TABLE PREDICTING VARIATIONS IN AGE DISCRIMINATION FORMAL COMPLAINTS IN U.S. FEDERAL AGENCIES [REVERSE CAUSALITY TESTS: INCLUSION OF ONE-YEAR AHEAD "ORGANIZATIONAL JUSTICE" CONTROL COVARIATE] ***
. 
. 
. 
. ** MODEL A1.1A: DISAGGREGATE SUPERVISOR/SUBORDINATE RATIO MEASURES [ratio_40over_suplb; ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS ***
. 
. xthybrid age_discrimination  ratio_40over_suplb  ratio_40over_nonsuplb   orgjustice_sem f1_orgjustice_sem   nonprof40over_tr_lb   politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10  ratio_55over_totallb, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio_40over_suplb  ratio_40over_nonsuplb    orgjustice_sem  f1_orgjustice_sem  nonprof40over_tr_lb   politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       718
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       125

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       5.7
{col 63}{txt}max{col 67}={res}{col 69}         9

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}27{txt}){col 67}={res}{col 70}  1252.46
{txt}Log pseudolikelihood = {res}-2279.0842{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:125} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0097293{col 26}{space 2} .0491979{col 37}{space 1}    0.20{col 46}{space 3}0.843{col 54}{space 4}-.0866967{col 67}{space 3} .1061553
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2} .0017906{col 26}{space 2} .0515817{col 37}{space 1}    0.03{col 46}{space 3}0.972{col 54}{space 4}-.0993076{col 67}{space 3} .1028889
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0426477{col 26}{space 2} .0657817{col 37}{space 1}   -0.65{col 46}{space 3}0.517{col 54}{space 4}-.1715775{col 67}{space 3} .0862821
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2}-.0572483{col 26}{space 2} .0789613{col 37}{space 1}   -0.73{col 46}{space 3}0.468{col 54}{space 4}-.2120095{col 67}{space 3}  .097513
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0445412{col 26}{space 2} .0754234{col 37}{space 1}    0.59{col 46}{space 3}0.555{col 54}{space 4}-.1032859{col 67}{space 3} .1923683
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0923386{col 26}{space 2} .0780987{col 37}{space 1}    1.18{col 46}{space 3}0.237{col 54}{space 4}-.0607321{col 67}{space 3} .2454093
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2} -.020638{col 26}{space 2}  .086964{col 37}{space 1}   -0.24{col 46}{space 3}0.812{col 54}{space 4}-.1910843{col 67}{space 3} .1498083
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2} .0307588{col 26}{space 2} .0852399{col 37}{space 1}    0.36{col 46}{space 3}0.718{col 54}{space 4}-.1363083{col 67}{space 3} .1978259
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8436216{col 26}{space 2} .0340338{col 37}{space 1}   24.79{col 46}{space 3}0.000{col 54}{space 4} .7769164{col 67}{space 3} .9103267
{txt}W__ra~_suplb {c |}{col 14}{res}{space 2} .1931824{col 26}{space 2} 1.299924{col 37}{space 1}    0.15{col 46}{space 3}0.882{col 54}{space 4}-2.354622{col 67}{space 3} 2.740987
{txt}W__ra~nsuplb {c |}{col 14}{res}{space 2} 1.685638{col 26}{space 2} 1.613831{col 37}{space 1}    1.04{col 46}{space 3}0.296{col 54}{space 4}-1.477412{col 67}{space 3} 4.848689
{txt}W__orgjust~m {c |}{col 14}{res}{space 2} .3655737{col 26}{space 2} .3442813{col 37}{space 1}    1.06{col 46}{space 3}0.288{col 54}{space 4}-.3092053{col 67}{space 3} 1.040353
{txt}W__f1_orgj~m {c |}{col 14}{res}{space 2}-.1526262{col 26}{space 2} .2450526{col 37}{space 1}   -0.62{col 46}{space 3}0.533{col 54}{space 4}-.6329205{col 67}{space 3} .3276682
{txt}W__nonprof~b {c |}{col 14}{res}{space 2}-1.490094{col 26}{space 2} 1.943396{col 37}{space 1}   -0.77{col 46}{space 3}0.443{col 54}{space 4} -5.29908{col 67}{space 3} 2.318893
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.379393{col 26}{space 2} 1.896305{col 37}{space 1}   -0.73{col 46}{space 3}0.467{col 54}{space 4}-5.096082{col 67}{space 3} 2.337296
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .0267069{col 26}{space 2} .2857065{col 37}{space 1}    0.09{col 46}{space 3}0.926{col 54}{space 4}-.5332676{col 67}{space 3} .5866814
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.3818095{col 26}{space 2} .0814084{col 37}{space 1}   -4.69{col 46}{space 3}0.000{col 54}{space 4}-.5413671{col 67}{space 3} -.222252
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.612516{col 26}{space 2} 1.169639{col 37}{space 1}    1.38{col 46}{space 3}0.168{col 54}{space 4}-.6799333{col 67}{space 3} 3.904966
{txt}B__ra~_suplb {c |}{col 14}{res}{space 2} -2.07041{col 26}{space 2} .8713374{col 37}{space 1}   -2.38{col 46}{space 3}0.017{col 54}{space 4}-3.778199{col 67}{space 3}-.3626197
{txt}B__ra~nsuplb {c |}{col 14}{res}{space 2} 1.766529{col 26}{space 2} 1.096665{col 37}{space 1}    1.61{col 46}{space 3}0.107{col 54}{space 4}-.3828958{col 67}{space 3} 3.915954
{txt}B__orgjust~m {c |}{col 14}{res}{space 2} .3107537{col 26}{space 2} 1.561172{col 37}{space 1}    0.20{col 46}{space 3}0.842{col 54}{space 4}-2.749086{col 67}{space 3} 3.370594
{txt}B__f1_orgj~m {c |}{col 14}{res}{space 2}-1.657927{col 26}{space 2} 1.497874{col 37}{space 1}   -1.11{col 46}{space 3}0.268{col 54}{space 4}-4.593705{col 67}{space 3} 1.277851
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .2169921{col 26}{space 2} .2724058{col 37}{space 1}    0.80{col 46}{space 3}0.426{col 54}{space 4}-.3169135{col 67}{space 3} .7508977
{txt}B__politic~b {c |}{col 14}{res}{space 2} .0788483{col 26}{space 2} .8596311{col 37}{space 1}    0.09{col 46}{space 3}0.927{col 54}{space 4}-1.605998{col 67}{space 3} 1.763694
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2506628{col 26}{space 2} .0994288{col 37}{space 1}    2.52{col 46}{space 3}0.012{col 54}{space 4}  .055786{col 67}{space 3} .4455395
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0238248{col 26}{space 2} .0573623{col 37}{space 1}   -0.42{col 46}{space 3}0.678{col 54}{space 4}-.1362528{col 67}{space 3} .0886033
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2} -.381767{col 26}{space 2} .9273173{col 37}{space 1}   -0.41{col 46}{space 3}0.681{col 54}{space 4}-2.199276{col 67}{space 3} 1.435742
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.353621{col 26}{space 2} .7694395{col 37}{space 1}   -5.66{col 46}{space 3}0.000{col 54}{space 4}-5.861694{col 67}{space 3}-2.845547
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.275976{col 26}{space 2} .1864229{col 54}{space 4}-3.641358{col 67}{space 3}-2.910594
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1478607{col 26}{space 2} .0293742{col 54}{space 4} .1001732{col 67}{space 3} .2182498
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       718{col 27}        .{col 38}-2279.084{col 49}    30{col 58} 4618.168{col 69} 4755.462
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
. *
. 
. ** COMPUTE IRR [EXPONENTIATED] MARGINAL EFFECT FOR PROCEDURAL FAIRNESS BASED ON BETWEEN INTERDECILE CHANGE IN COVARIATE **
. lincom _b[B__orgjustice_sem]*0.2659021 - _b[B__orgjustice_sem]*-0.1089841, eform

{p 0 7}{space 1}{text:( 1)}{space 1} {res}.3748862{res}*{res}[age_discrimination]B__orgjustice_sem = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}age_discri~n{col 14}{c |}     exp(b){col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.123554{col 26}{space 2} .6575734{col 37}{space 1}    0.20{col 46}{space 3}0.842{col 54}{space 4} .3567948{col 67}{space 3} 3.538097
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. *
. 
. **  MODEL A1.1B: RATIO OF OVER40 SUPERVISORS TO OVER40 NON-SUPERVISORS [RATIO OF ratio_40over_suplb TO ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS ***
. 
. xthybrid age_discrimination  ratio40suplb_nonsuplb    orgjustice_sem  f1_orgjustice_sem  nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10  ratio_55over_totallb, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio40suplb_nonsuplb   orgjustice_sem  f1_orgjustice_sem   nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup  ratio_minsup_nonmsup  ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       718
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       125

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       5.7
{col 63}{txt}max{col 67}={res}{col 69}         9

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}25{txt}){col 67}={res}{col 70}  1218.10
{txt}Log pseudolikelihood = {res}-2278.8311{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:125} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0048998{col 26}{space 2} .0493274{col 37}{space 1}    0.10{col 46}{space 3}0.921{col 54}{space 4}-.0917802{col 67}{space 3} .1015798
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2}-.0053417{col 26}{space 2} .0518867{col 37}{space 1}   -0.10{col 46}{space 3}0.918{col 54}{space 4}-.1070378{col 67}{space 3} .0963545
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0547422{col 26}{space 2} .0657541{col 37}{space 1}   -0.83{col 46}{space 3}0.405{col 54}{space 4}-.1836178{col 67}{space 3} .0741334
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2} -.074748{col 26}{space 2} .0775951{col 37}{space 1}   -0.96{col 46}{space 3}0.335{col 54}{space 4}-.2268317{col 67}{space 3} .0773357
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0183679{col 26}{space 2} .0740508{col 37}{space 1}    0.25{col 46}{space 3}0.804{col 54}{space 4} -.126769{col 67}{space 3} .1635047
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0608617{col 26}{space 2} .0779052{col 37}{space 1}    0.78{col 46}{space 3}0.435{col 54}{space 4}-.0918296{col 67}{space 3}  .213553
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0536864{col 26}{space 2} .0861769{col 37}{space 1}   -0.62{col 46}{space 3}0.533{col 54}{space 4}-.2225899{col 67}{space 3} .1152172
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2}-.0010506{col 26}{space 2}  .084169{col 37}{space 1}   -0.01{col 46}{space 3}0.990{col 54}{space 4}-.1660189{col 67}{space 3} .1639177
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}        0{col 26}{txt}  (omitted)
{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8458705{col 26}{space 2} .0342122{col 37}{space 1}   24.72{col 46}{space 3}0.000{col 54}{space 4} .7788158{col 67}{space 3} .9129251
{txt}W__ratio40~b {c |}{col 14}{res}{space 2}-.5759057{col 26}{space 2} .4759998{col 37}{space 1}   -1.21{col 46}{space 3}0.226{col 54}{space 4}-1.508848{col 67}{space 3} .3570367
{txt}W__orgjust~m {c |}{col 14}{res}{space 2} .3798213{col 26}{space 2} .3450491{col 37}{space 1}    1.10{col 46}{space 3}0.271{col 54}{space 4}-.2964626{col 67}{space 3} 1.056105
{txt}W__f1_orgj~m {c |}{col 14}{res}{space 2}-.1504704{col 26}{space 2} .2510865{col 37}{space 1}   -0.60{col 46}{space 3}0.549{col 54}{space 4}-.6425908{col 67}{space 3} .3416501
{txt}W__nonprof~b {c |}{col 14}{res}{space 2}-.5728147{col 26}{space 2} 1.174979{col 37}{space 1}   -0.49{col 46}{space 3}0.626{col 54}{space 4}-2.875731{col 67}{space 3} 1.730102
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.569814{col 26}{space 2} 1.946117{col 37}{space 1}   -0.81{col 46}{space 3}0.420{col 54}{space 4}-5.384132{col 67}{space 3} 2.244505
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .0559149{col 26}{space 2} .2868616{col 37}{space 1}    0.19{col 46}{space 3}0.845{col 54}{space 4}-.5063234{col 67}{space 3} .6181533
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.3817455{col 26}{space 2} .0757078{col 37}{space 1}   -5.04{col 46}{space 3}0.000{col 54}{space 4}-.5301301{col 67}{space 3} -.233361
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2}   1.7813{col 26}{space 2} 1.149336{col 37}{space 1}    1.55{col 46}{space 3}0.121{col 54}{space 4} -.471357{col 67}{space 3} 4.033956
{txt}B__ratio40~b {c |}{col 14}{res}{space 2}-.9891208{col 26}{space 2} .4956037{col 37}{space 1}   -2.00{col 46}{space 3}0.046{col 54}{space 4}-1.960486{col 67}{space 3}-.0177554
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}  .267357{col 26}{space 2}  1.54626{col 37}{space 1}    0.17{col 46}{space 3}0.863{col 54}{space 4}-2.763258{col 67}{space 3} 3.297972
{txt}B__f1_orgj~m {c |}{col 14}{res}{space 2}-1.698155{col 26}{space 2} 1.474961{col 37}{space 1}   -1.15{col 46}{space 3}0.250{col 54}{space 4}-4.589024{col 67}{space 3} 1.192715
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .2022322{col 26}{space 2} .2772079{col 37}{space 1}    0.73{col 46}{space 3}0.466{col 54}{space 4}-.3410854{col 67}{space 3} .7455497
{txt}B__politic~b {c |}{col 14}{res}{space 2} .1060119{col 26}{space 2} .8612733{col 37}{space 1}    0.12{col 46}{space 3}0.902{col 54}{space 4}-1.582053{col 67}{space 3} 1.794077
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2647128{col 26}{space 2} .0989866{col 37}{space 1}    2.67{col 46}{space 3}0.007{col 54}{space 4} .0707026{col 67}{space 3} .4587229
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0254506{col 26}{space 2} .0588246{col 37}{space 1}   -0.43{col 46}{space 3}0.665{col 54}{space 4}-.1407448{col 67}{space 3} .0898435
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.7969644{col 26}{space 2} .7257933{col 37}{space 1}   -1.10{col 46}{space 3}0.272{col 54}{space 4}-2.219493{col 67}{space 3} .6255643
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.557083{col 26}{space 2} 1.006802{col 37}{space 1}   -3.53{col 46}{space 3}0.000{col 54}{space 4}-5.530378{col 67}{space 3}-1.583788
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.278514{col 26}{space 2} .1871298{col 54}{space 4}-3.645282{col 67}{space 3}-2.911746
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1489195{col 26}{space 2} .0302651{col 54}{space 4}  .099991{col 67}{space 3} .2217903
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       718{col 27}        .{col 38}-2278.831{col 49}    28{col 58} 4613.662{col 69} 4741.803
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
. *
. *
. 
. 
. ** COMPUTE IRR [EXPONENTIATED] MARGINAL EFFECT FOR PROCEDURAL FAIRNESS BASED ON BETWEEN INTERDECILE CHANGE IN COVARIATE **
. 
. lincom _b[B__orgjustice_sem]*0.2659021 - _b[B__orgjustice_sem]*-0.1089841, eform

{p 0 7}{space 1}{text:( 1)}{space 1} {res}.3748862{res}*{res}[age_discrimination]B__orgjustice_sem = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}age_discri~n{col 14}{c |}     exp(b){col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 1.105423{col 26}{space 2} .6407827{col 37}{space 1}    0.17{col 46}{space 3}0.863{col 54}{space 4} .3549043{col 67}{space 3} 3.443072
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. *** THE ORGANIZATIONAL JUSTICE/PROCEDURAL FAIRNESS BETWEEN-EFFECT IS ATTENUATED IN MAGNITUDE AND ESTIMATED WITH IMPRECISION [LOSE SIGNIFICANCE] DUE TO COLLINEARITY WITH PRE-DETERMINED "LEAD" VERSION OF COVARIATE ***
. *** NOTE: DATA IS NOT SUFFICIENTLY RICH ENOUGH TO DISCRIMINATE THESE CONTEMPORANEOUS AND LEAD ORGANIZATIONAL JUSTICE EFFECTS ON AGE DISCRIMINATION FORMAL COMPLAINTS *** 
. 
. correlate orgjustice_sem  f1_orgjustice_sem
{txt}(obs=718)

             {c |} orgjus~m f1_org~m
{hline 13}{c +}{hline 18}
orgjustice~m {c |}{res}   1.0000
{txt}f1_orgjust~m {c |}{res}   0.9285   1.0000

{txt}
{com}. 
. 
. 
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
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. 
. 
. 
. 
. *** TABLE A1.2: APPENDIX SECTION 1B: MODEL SPECIFICATIONS DROPPING VETERANS AFFAIRS; DROPPING EXTREME CASES OF THE MAIN COVARIATES & DEPENDENT VARIABLE ****  
. 
. 
. 
. ** MODEL A1.2A: DISAGGREGATE SUPERVISOR/SUBORDINATE RATIO MEASURES [ratio_40over_suplb; ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS ***
. 
. xthybrid age_discrimination  ratio_40over_suplb  ratio_40over_nonsuplb   orgjustice_sem   nonprof40over_tr_lb   politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 ratio_55over_totallb  if a_id!=99 & a_id!=100 & a_id!=101, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio_40over_suplb  ratio_40over_nonsuplb    orgjustice_sem   nonprof40over_tr_lb   politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       876
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       127

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}26{txt}){col 67}={res}{col 70}  1217.38
{txt}Log pseudolikelihood = {res}-2633.5203{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:127} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0386928{col 26}{space 2} .0411913{col 37}{space 1}    0.94{col 46}{space 3}0.348{col 54}{space 4}-.0420407{col 67}{space 3} .1194264
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2} .0291224{col 26}{space 2} .0499393{col 37}{space 1}    0.58{col 46}{space 3}0.560{col 54}{space 4}-.0687569{col 67}{space 3} .1270017
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0176044{col 26}{space 2} .0584059{col 37}{space 1}   -0.30{col 46}{space 3}0.763{col 54}{space 4}-.1320779{col 67}{space 3} .0968692
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2} -.030204{col 26}{space 2} .0751649{col 37}{space 1}   -0.40{col 46}{space 3}0.688{col 54}{space 4}-.1775246{col 67}{space 3} .1171165
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0565446{col 26}{space 2} .0702127{col 37}{space 1}    0.81{col 46}{space 3}0.421{col 54}{space 4}-.0810698{col 67}{space 3}  .194159
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .1066097{col 26}{space 2} .0743283{col 37}{space 1}    1.43{col 46}{space 3}0.151{col 54}{space 4}-.0390711{col 67}{space 3} .2522906
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2} .0067143{col 26}{space 2} .0802711{col 37}{space 1}    0.08{col 46}{space 3}0.933{col 54}{space 4}-.1506142{col 67}{space 3} .1640428
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2} .0483697{col 26}{space 2} .0790024{col 37}{space 1}    0.61{col 46}{space 3}0.540{col 54}{space 4}-.1064722{col 67}{space 3} .2032116
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2} .0158537{col 26}{space 2} .0911807{col 37}{space 1}    0.17{col 46}{space 3}0.862{col 54}{space 4}-.1628571{col 67}{space 3} .1945646
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8430413{col 26}{space 2} .0335899{col 37}{space 1}   25.10{col 46}{space 3}0.000{col 54}{space 4} .7772063{col 67}{space 3} .9088762
{txt}W__ra~_suplb {c |}{col 14}{res}{space 2} -1.17844{col 26}{space 2} 1.101585{col 37}{space 1}   -1.07{col 46}{space 3}0.285{col 54}{space 4}-3.337506{col 67}{space 3} .9806257
{txt}W__ra~nsuplb {c |}{col 14}{res}{space 2} .4279223{col 26}{space 2}  1.15296{col 37}{space 1}    0.37{col 46}{space 3}0.711{col 54}{space 4}-1.831839{col 67}{space 3} 2.687683
{txt}W__orgjust~m {c |}{col 14}{res}{space 2}-.1880549{col 26}{space 2} .2065803{col 37}{space 1}   -0.91{col 46}{space 3}0.363{col 54}{space 4}-.5929448{col 67}{space 3}  .216835
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} .8040714{col 26}{space 2} 1.436363{col 37}{space 1}    0.56{col 46}{space 3}0.576{col 54}{space 4}-2.011147{col 67}{space 3}  3.61929
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.147306{col 26}{space 2}  1.55994{col 37}{space 1}   -0.74{col 46}{space 3}0.462{col 54}{space 4}-4.204732{col 67}{space 3}  1.91012
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .2241997{col 26}{space 2} .2411516{col 37}{space 1}    0.93{col 46}{space 3}0.353{col 54}{space 4}-.2484486{col 67}{space 3} .6968481
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.4195026{col 26}{space 2} .0964542{col 37}{space 1}   -4.35{col 46}{space 3}0.000{col 54}{space 4}-.6085493{col 67}{space 3}-.2304559
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2}  1.42637{col 26}{space 2} .9814852{col 37}{space 1}    1.45{col 46}{space 3}0.146{col 54}{space 4}-.4973055{col 67}{space 3} 3.350046
{txt}B__ra~_suplb {c |}{col 14}{res}{space 2}-1.948657{col 26}{space 2}  .844464{col 37}{space 1}   -2.31{col 46}{space 3}0.021{col 54}{space 4}-3.603776{col 67}{space 3}-.2935382
{txt}B__ra~nsuplb {c |}{col 14}{res}{space 2} 1.726047{col 26}{space 2} .9711658{col 37}{space 1}    1.78{col 46}{space 3}0.076{col 54}{space 4}-.1774033{col 67}{space 3} 3.629497
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.503313{col 26}{space 2} .3259429{col 37}{space 1}   -4.61{col 46}{space 3}0.000{col 54}{space 4} -2.14215{col 67}{space 3}-.8644769
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1643669{col 26}{space 2} .2623792{col 37}{space 1}    0.63{col 46}{space 3}0.531{col 54}{space 4} -.349887{col 67}{space 3} .6786207
{txt}B__politic~b {c |}{col 14}{res}{space 2}-.6851452{col 26}{space 2} .9386845{col 37}{space 1}   -0.73{col 46}{space 3}0.465{col 54}{space 4}-2.524933{col 67}{space 3} 1.154643
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2469541{col 26}{space 2} .0949364{col 37}{space 1}    2.60{col 46}{space 3}0.009{col 54}{space 4} .0608822{col 67}{space 3}  .433026
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0345427{col 26}{space 2} .0566336{col 37}{space 1}   -0.61{col 46}{space 3}0.542{col 54}{space 4}-.1455424{col 67}{space 3} .0764571
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2} -.198738{col 26}{space 2} .8623197{col 37}{space 1}   -0.23{col 46}{space 3}0.818{col 54}{space 4}-1.888854{col 67}{space 3} 1.491378
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.456077{col 26}{space 2} .7626293{col 37}{space 1}   -5.84{col 46}{space 3}0.000{col 54}{space 4}-5.950803{col 67}{space 3}-2.961351
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.394485{col 26}{space 2} .2095484{col 54}{space 4}-3.805192{col 67}{space 3}-2.983777
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1534231{col 26}{space 2} .0296484{col 54}{space 4} .1050508{col 67}{space 3} .2240693
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       876{col 27}        .{col 38} -2633.52{col 49}    29{col 58} 5325.041{col 69} 5463.526
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
. *
. *
. *
. *
. *
. *
. 
. 
. 
. **  MODEL A1.2B: RATIO OF OVER40 SUPERVISORS TO OVER40 NON-SUPERVISORS [RATIO OF ratio_40over_suplb TO ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS ***
. 
. xthybrid age_discrimination  ratio40suplb_nonsuplb    orgjustice_sem   nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10  ratio_55over_totallb if a_id!=99 & a_id!=100 & a_id!=101 , clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio40suplb_nonsuplb   orgjustice_sem    nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       876
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       127

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}24{txt}){col 67}={res}{col 70}  1206.53
{txt}Log pseudolikelihood = {res}-2633.5991{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:127} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0381449{col 26}{space 2} .0411734{col 37}{space 1}    0.93{col 46}{space 3}0.354{col 54}{space 4}-.0425535{col 67}{space 3} .1188433
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2} .0286918{col 26}{space 2} .0499709{col 37}{space 1}    0.57{col 46}{space 3}0.566{col 54}{space 4}-.0692493{col 67}{space 3} .1266329
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2} -.018269{col 26}{space 2} .0581577{col 37}{space 1}   -0.31{col 46}{space 3}0.753{col 54}{space 4}-.1322561{col 67}{space 3}  .095718
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2}-.0315369{col 26}{space 2} .0751971{col 37}{space 1}   -0.42{col 46}{space 3}0.675{col 54}{space 4}-.1789206{col 67}{space 3} .1158468
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0567813{col 26}{space 2} .0691625{col 37}{space 1}    0.82{col 46}{space 3}0.412{col 54}{space 4}-.0787747{col 67}{space 3} .1923372
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .1054657{col 26}{space 2} .0768272{col 37}{space 1}    1.37{col 46}{space 3}0.170{col 54}{space 4}-.0451129{col 67}{space 3} .2560443
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2} .0037263{col 26}{space 2} .0824423{col 37}{space 1}    0.05{col 46}{space 3}0.964{col 54}{space 4}-.1578576{col 67}{space 3} .1653102
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2} .0468414{col 26}{space 2} .0811449{col 37}{space 1}    0.58{col 46}{space 3}0.564{col 54}{space 4}-.1121996{col 67}{space 3} .2058824
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}  .012495{col 26}{space 2} .0932522{col 37}{space 1}    0.13{col 46}{space 3}0.893{col 54}{space 4} -.170276{col 67}{space 3}  .195266
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8430488{col 26}{space 2} .0336821{col 37}{space 1}   25.03{col 46}{space 3}0.000{col 54}{space 4} .7770331{col 67}{space 3} .9090644
{txt}W__ratio40~b {c |}{col 14}{res}{space 2} -.457274{col 26}{space 2} .4120652{col 37}{space 1}   -1.11{col 46}{space 3}0.267{col 54}{space 4}-1.264907{col 67}{space 3} .3503589
{txt}W__orgjust~m {c |}{col 14}{res}{space 2}-.1667645{col 26}{space 2} .2131618{col 37}{space 1}   -0.78{col 46}{space 3}0.434{col 54}{space 4} -.584554{col 67}{space 3}  .251025
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} -.094495{col 26}{space 2} 1.052953{col 37}{space 1}   -0.09{col 46}{space 3}0.928{col 54}{space 4}-2.158244{col 67}{space 3} 1.969254
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.134151{col 26}{space 2} 1.547088{col 37}{space 1}   -0.73{col 46}{space 3}0.464{col 54}{space 4}-4.166388{col 67}{space 3} 1.898085
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .1900652{col 26}{space 2} .2373071{col 37}{space 1}    0.80{col 46}{space 3}0.423{col 54}{space 4}-.2750481{col 67}{space 3} .6551785
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2} -.404032{col 26}{space 2} .1029083{col 37}{space 1}   -3.93{col 46}{space 3}0.000{col 54}{space 4}-.6057284{col 67}{space 3}-.2023355
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.531597{col 26}{space 2} .9823733{col 37}{space 1}    1.56{col 46}{space 3}0.119{col 54}{space 4}-.3938191{col 67}{space 3} 3.457014
{txt}B__ratio40~b {c |}{col 14}{res}{space 2} -1.01549{col 26}{space 2} .4486815{col 37}{space 1}   -2.26{col 46}{space 3}0.024{col 54}{space 4} -1.89489{col 67}{space 3}-.1360906
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.581905{col 26}{space 2}  .311737{col 37}{space 1}   -5.07{col 46}{space 3}0.000{col 54}{space 4}-2.192898{col 67}{space 3}-.9709117
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1378662{col 26}{space 2} .2649684{col 37}{space 1}    0.52{col 46}{space 3}0.603{col 54}{space 4}-.3814622{col 67}{space 3} .6571947
{txt}B__politic~b {c |}{col 14}{res}{space 2}-.5902729{col 26}{space 2} .9484598{col 37}{space 1}   -0.62{col 46}{space 3}0.534{col 54}{space 4} -2.44922{col 67}{space 3} 1.268674
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2517464{col 26}{space 2} .0937815{col 37}{space 1}    2.68{col 46}{space 3}0.007{col 54}{space 4} .0679381{col 67}{space 3} .4355547
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0368144{col 26}{space 2} .0573615{col 37}{space 1}   -0.64{col 46}{space 3}0.521{col 54}{space 4}-.1492408{col 67}{space 3}  .075612
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.6118245{col 26}{space 2} .7316207{col 37}{space 1}   -0.84{col 46}{space 3}0.403{col 54}{space 4}-2.045775{col 67}{space 3} .8221257
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.531237{col 26}{space 2} .9245711{col 37}{space 1}   -3.82{col 46}{space 3}0.000{col 54}{space 4}-5.343363{col 67}{space 3}-1.719111
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2} -3.39084{col 26}{space 2} .2112593{col 54}{space 4}-3.804901{col 67}{space 3}-2.976779
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2}  .153014{col 26}{space 2} .0297062{col 54}{space 4} .1045872{col 67}{space 3} .2238638
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       876{col 27}        .{col 38}-2633.599{col 49}    27{col 58} 5321.198{col 69} 5450.133
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}.    
.    
. 
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. 
. ** MODEL A1.2C: DISAGGREGATE SUPERVISOR/SUBORDINATE RATIO MEASURES [ratio_40over_suplb; ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS [EXCLUDE VALUES OF DEPENDENT VARIABLE "AGE-DSICRIMINATION" EXCEEDING 99TH PERCENTILE VALUE [X > 386] ***
. 
. xthybrid age_discrimination  ratio_40over_suplb  ratio_40over_nonsuplb   orgjustice_sem   nonprof40over_tr_lb   politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 ratio_55over_totallb  if age_discrimination <= 386, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio_40over_suplb  ratio_40over_nonsuplb    orgjustice_sem   nonprof40over_tr_lb   politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       889
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       129

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}26{txt}){col 67}={res}{col 70}  1261.30
{txt}Log pseudolikelihood = {res}-2685.5703{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:129} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0157301{col 26}{space 2} .0446548{col 37}{space 1}    0.35{col 46}{space 3}0.725{col 54}{space 4}-.0717917{col 67}{space 3}  .103252
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2} .0078447{col 26}{space 2} .0521527{col 37}{space 1}    0.15{col 46}{space 3}0.880{col 54}{space 4}-.0943728{col 67}{space 3} .1100622
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0439273{col 26}{space 2} .0623239{col 37}{space 1}   -0.70{col 46}{space 3}0.481{col 54}{space 4}-.1660799{col 67}{space 3} .0782252
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2} -.049534{col 26}{space 2} .0760119{col 37}{space 1}   -0.65{col 46}{space 3}0.515{col 54}{space 4}-.1985146{col 67}{space 3} .0994466
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0364087{col 26}{space 2} .0712742{col 37}{space 1}    0.51{col 46}{space 3}0.609{col 54}{space 4}-.1032862{col 67}{space 3} .1761036
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0867561{col 26}{space 2} .0757101{col 37}{space 1}    1.15{col 46}{space 3}0.252{col 54}{space 4} -.061633{col 67}{space 3} .2351453
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0190644{col 26}{space 2} .0815205{col 37}{space 1}   -0.23{col 46}{space 3}0.815{col 54}{space 4}-.1788417{col 67}{space 3} .1407129
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2}  .035012{col 26}{space 2}  .079832{col 37}{space 1}    0.44{col 46}{space 3}0.661{col 54}{space 4}-.1214558{col 67}{space 3} .1914798
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2} .0042715{col 26}{space 2} .0904357{col 37}{space 1}    0.05{col 46}{space 3}0.962{col 54}{space 4}-.1729792{col 67}{space 3} .1815222
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8398891{col 26}{space 2} .0331916{col 37}{space 1}   25.30{col 46}{space 3}0.000{col 54}{space 4} .7748347{col 67}{space 3} .9049435
{txt}W__ra~_suplb {c |}{col 14}{res}{space 2}-.5799782{col 26}{space 2} 1.168568{col 37}{space 1}   -0.50{col 46}{space 3}0.620{col 54}{space 4}-2.870328{col 67}{space 3} 1.710372
{txt}W__ra~nsuplb {c |}{col 14}{res}{space 2}  .172904{col 26}{space 2} 1.187932{col 37}{space 1}    0.15{col 46}{space 3}0.884{col 54}{space 4}-2.155401{col 67}{space 3} 2.501209
{txt}W__orgjust~m {c |}{col 14}{res}{space 2}-.0296539{col 26}{space 2} .2534596{col 37}{space 1}   -0.12{col 46}{space 3}0.907{col 54}{space 4}-.5264256{col 67}{space 3} .4671177
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} .5732889{col 26}{space 2} 1.458816{col 37}{space 1}    0.39{col 46}{space 3}0.694{col 54}{space 4}-2.285938{col 67}{space 3} 3.432516
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.309685{col 26}{space 2} 1.553382{col 37}{space 1}   -0.84{col 46}{space 3}0.399{col 54}{space 4}-4.354257{col 67}{space 3} 1.734888
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .2147743{col 26}{space 2} .2394122{col 37}{space 1}    0.90{col 46}{space 3}0.370{col 54}{space 4}-.2544649{col 67}{space 3} .6840136
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.4134656{col 26}{space 2} .0957599{col 37}{space 1}   -4.32{col 46}{space 3}0.000{col 54}{space 4}-.6011515{col 67}{space 3}-.2257796
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2}  1.71452{col 26}{space 2} 1.012474{col 37}{space 1}    1.69{col 46}{space 3}0.090{col 54}{space 4}-.2698934{col 67}{space 3} 3.698932
{txt}B__ra~_suplb {c |}{col 14}{res}{space 2}-1.971077{col 26}{space 2} .7876558{col 37}{space 1}   -2.50{col 46}{space 3}0.012{col 54}{space 4}-3.514854{col 67}{space 3}-.4273002
{txt}B__ra~nsuplb {c |}{col 14}{res}{space 2} 1.722723{col 26}{space 2} .9471723{col 37}{space 1}    1.82{col 46}{space 3}0.069{col 54}{space 4} -.133701{col 67}{space 3} 3.579146
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.491547{col 26}{space 2} .3232814{col 37}{space 1}   -4.61{col 46}{space 3}0.000{col 54}{space 4}-2.125167{col 67}{space 3}-.8579272
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1746439{col 26}{space 2} .2589112{col 37}{space 1}    0.67{col 46}{space 3}0.500{col 54}{space 4}-.3328128{col 67}{space 3} .6821006
{txt}B__politic~b {c |}{col 14}{res}{space 2} -.705073{col 26}{space 2} .9347911{col 37}{space 1}   -0.75{col 46}{space 3}0.451{col 54}{space 4} -2.53723{col 67}{space 3} 1.127084
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2409454{col 26}{space 2} .0935494{col 37}{space 1}    2.58{col 46}{space 3}0.010{col 54}{space 4} .0575921{col 67}{space 3} .4242988
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0342251{col 26}{space 2} .0565615{col 37}{space 1}   -0.61{col 46}{space 3}0.545{col 54}{space 4}-.1450837{col 67}{space 3} .0766335
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.1819465{col 26}{space 2} .8519672{col 37}{space 1}   -0.21{col 46}{space 3}0.831{col 54}{space 4}-1.851772{col 67}{space 3} 1.487879
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.392919{col 26}{space 2} .7454889{col 37}{space 1}   -5.89{col 46}{space 3}0.000{col 54}{space 4} -5.85405{col 67}{space 3}-2.931787
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.281779{col 26}{space 2} .2039603{col 54}{space 4}-3.681534{col 67}{space 3}-2.882025
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1493372{col 26}{space 2} .0290394{col 54}{space 4} .1020111{col 67}{space 3} .2186193
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       889{col 27}        .{col 38} -2685.57{col 49}    29{col 58} 5429.141{col 69} 5568.053
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
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. **  MODEL A1.2D: RATIO OF OVER40 SUPERVISORS TO OVER40 NON-SUPERVISORS [RATIO OF ratio_40over_suplb TO ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS [EXCLUDE VALUES OF DEPENDENT VARIABLE "AGE-DSICRIMINATION" EXCEEDING 99TH PERCENTILE VALUE [X > 386] ***
. 
. xthybrid age_discrimination  ratio40suplb_nonsuplb    orgjustice_sem   nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 ratio_55over_totallb  if age_discrimination <= 386, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio40suplb_nonsuplb   orgjustice_sem    nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       889
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       129

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}24{txt}){col 67}={res}{col 70}  1240.18
{txt}Log pseudolikelihood = {res}-2685.1525{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:129} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2} .0146315{col 26}{space 2} .0449131{col 37}{space 1}    0.33{col 46}{space 3}0.745{col 54}{space 4}-.0733965{col 67}{space 3} .1026595
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2} .0056875{col 26}{space 2} .0529395{col 37}{space 1}    0.11{col 46}{space 3}0.914{col 54}{space 4}-.0980719{col 67}{space 3}  .109447
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0475754{col 26}{space 2} .0631552{col 37}{space 1}   -0.75{col 46}{space 3}0.451{col 54}{space 4}-.1713572{col 67}{space 3} .0762064
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2} -.054457{col 26}{space 2} .0764234{col 37}{space 1}   -0.71{col 46}{space 3}0.476{col 54}{space 4}-.2042442{col 67}{space 3} .0953302
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0311678{col 26}{space 2} .0711182{col 37}{space 1}    0.44{col 46}{space 3}0.661{col 54}{space 4}-.1082213{col 67}{space 3} .1705569
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0794462{col 26}{space 2} .0788292{col 37}{space 1}    1.01{col 46}{space 3}0.314{col 54}{space 4}-.0750561{col 67}{space 3} .2339485
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0278004{col 26}{space 2} .0844121{col 37}{space 1}   -0.33{col 46}{space 3}0.742{col 54}{space 4}-.1932451{col 67}{space 3} .1376444
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2}  .026389{col 26}{space 2} .0824509{col 37}{space 1}    0.32{col 46}{space 3}0.749{col 54}{space 4}-.1352117{col 67}{space 3} .1879897
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}-.0056981{col 26}{space 2} .0928799{col 37}{space 1}   -0.06{col 46}{space 3}0.951{col 54}{space 4}-.1877393{col 67}{space 3} .1763432
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8408878{col 26}{space 2}  .033294{col 37}{space 1}   25.26{col 46}{space 3}0.000{col 54}{space 4} .7756327{col 67}{space 3} .9061429
{txt}W__ratio40~b {c |}{col 14}{res}{space 2} -.342608{col 26}{space 2} .4210138{col 37}{space 1}   -0.81{col 46}{space 3}0.416{col 54}{space 4} -1.16778{col 67}{space 3} .4825639
{txt}W__orgjust~m {c |}{col 14}{res}{space 2}-.0200514{col 26}{space 2} .2536655{col 37}{space 1}   -0.08{col 46}{space 3}0.937{col 54}{space 4}-.5172267{col 67}{space 3} .4771238
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} -.086439{col 26}{space 2} 1.024477{col 37}{space 1}   -0.08{col 46}{space 3}0.933{col 54}{space 4}-2.094377{col 67}{space 3} 1.921499
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.313074{col 26}{space 2} 1.545155{col 37}{space 1}   -0.85{col 46}{space 3}0.395{col 54}{space 4}-4.341521{col 67}{space 3} 1.715374
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .1949276{col 26}{space 2} .2359538{col 37}{space 1}    0.83{col 46}{space 3}0.409{col 54}{space 4}-.2675334{col 67}{space 3} .6573886
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.4054442{col 26}{space 2} .0976891{col 37}{space 1}   -4.15{col 46}{space 3}0.000{col 54}{space 4}-.5969113{col 67}{space 3}-.2139771
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.739441{col 26}{space 2} .9957938{col 37}{space 1}    1.75{col 46}{space 3}0.081{col 54}{space 4}-.2122794{col 67}{space 3} 3.691161
{txt}B__ratio40~b {c |}{col 14}{res}{space 2}-1.021116{col 26}{space 2} .4240318{col 37}{space 1}   -2.41{col 46}{space 3}0.016{col 54}{space 4}-1.852203{col 67}{space 3}-.1900287
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.570093{col 26}{space 2} .3094837{col 37}{space 1}   -5.07{col 46}{space 3}0.000{col 54}{space 4} -2.17667{col 67}{space 3}-.9635161
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1492843{col 26}{space 2}  .262264{col 37}{space 1}    0.57{col 46}{space 3}0.569{col 54}{space 4}-.3647436{col 67}{space 3} .6633123
{txt}B__politic~b {c |}{col 14}{res}{space 2} -.609871{col 26}{space 2} .9465138{col 37}{space 1}   -0.64{col 46}{space 3}0.519{col 54}{space 4}-2.465004{col 67}{space 3} 1.245262
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2472872{col 26}{space 2} .0922967{col 37}{space 1}    2.68{col 46}{space 3}0.007{col 54}{space 4}  .066389{col 67}{space 3} .4281854
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0366089{col 26}{space 2} .0573115{col 37}{space 1}   -0.64{col 46}{space 3}0.523{col 54}{space 4}-.1489374{col 67}{space 3} .0757195
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2} -.612853{col 26}{space 2} .6947035{col 37}{space 1}   -0.88{col 46}{space 3}0.378{col 54}{space 4}-1.974447{col 67}{space 3} .7487409
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.483779{col 26}{space 2} .8907814{col 37}{space 1}   -3.91{col 46}{space 3}0.000{col 54}{space 4}-5.229679{col 67}{space 3} -1.73788
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.284025{col 26}{space 2} .2041804{col 54}{space 4}-3.684211{col 67}{space 3}-2.883838
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1491807{col 26}{space 2} .0291306{col 54}{space 4} .1017415{col 67}{space 3} .2187397
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       889{col 27}        .{col 38}-2685.152{col 49}    27{col 58} 5424.305{col 69} 5553.638
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}.    
. 
. *****************************************************************************************************************************************************************************************
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. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. *****************************************************************************************************************************************************************************************
. 
. 
. 
. 
. ** MODEL A1.2E: DISAGGREGATE SUPERVISOR/SUBORDINATE RATIO MEASURES [ratio_40over_suplb; ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS [EXCLUDE VALUES OF KEY COVARIATE "ratio_40over_suplb" EXCEEDING THE 1ST AND 99TH PERCENTILE VALUE] ***
. 
. xthybrid age_discrimination ratio_40over_suplb    ratio_40over_nonsuplb  orgjustice_sem    nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10  ratio_55over_totallb if ratio_40over_suplb>= 0.7095544 & ratio_40over_suplb<= 0.969697, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) ///
> full use(ratio_40over_suplb    ratio_40over_nonsuplb   orgjustice_sem  nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb)

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       880
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       129

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.8
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}26{txt}){col 67}={res}{col 70}  1422.72
{txt}Log pseudolikelihood = {res}-2692.9495{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:129} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2}-.0076943{col 26}{space 2} .0476881{col 37}{space 1}   -0.16{col 46}{space 3}0.872{col 54}{space 4}-.1011613{col 67}{space 3} .0857727
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2}-.0078781{col 26}{space 2} .0534411{col 37}{space 1}   -0.15{col 46}{space 3}0.883{col 54}{space 4}-.1126207{col 67}{space 3} .0968646
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0630856{col 26}{space 2} .0636583{col 37}{space 1}   -0.99{col 46}{space 3}0.322{col 54}{space 4}-.1878535{col 67}{space 3} .0616824
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2}-.0663477{col 26}{space 2} .0763655{col 37}{space 1}   -0.87{col 46}{space 3}0.385{col 54}{space 4}-.2160214{col 67}{space 3} .0833259
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0223246{col 26}{space 2} .0715157{col 37}{space 1}    0.31{col 46}{space 3}0.755{col 54}{space 4}-.1178435{col 67}{space 3} .1624927
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0698248{col 26}{space 2} .0747758{col 37}{space 1}    0.93{col 46}{space 3}0.350{col 54}{space 4}-.0767331{col 67}{space 3} .2163827
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0278583{col 26}{space 2} .0784823{col 37}{space 1}   -0.35{col 46}{space 3}0.723{col 54}{space 4}-.1816808{col 67}{space 3} .1259641
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2}  .024433{col 26}{space 2} .0804856{col 37}{space 1}    0.30{col 46}{space 3}0.761{col 54}{space 4} -.133316{col 67}{space 3} .1821819
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}-.0115257{col 26}{space 2} .0899734{col 37}{space 1}   -0.13{col 46}{space 3}0.898{col 54}{space 4}-.1878703{col 67}{space 3} .1648189
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8413774{col 26}{space 2} .0315018{col 37}{space 1}   26.71{col 46}{space 3}0.000{col 54}{space 4}  .779635{col 67}{space 3} .9031198
{txt}W__ra~_suplb {c |}{col 14}{res}{space 2}-.2521566{col 26}{space 2} 1.163873{col 37}{space 1}   -0.22{col 46}{space 3}0.828{col 54}{space 4}-2.533307{col 67}{space 3} 2.028993
{txt}W__ra~nsuplb {c |}{col 14}{res}{space 2} .3567257{col 26}{space 2} 1.185265{col 37}{space 1}    0.30{col 46}{space 3}0.763{col 54}{space 4}-1.966352{col 67}{space 3} 2.679803
{txt}W__orgjust~m {c |}{col 14}{res}{space 2} .0901658{col 26}{space 2}  .255982{col 37}{space 1}    0.35{col 46}{space 3}0.725{col 54}{space 4}-.4115496{col 67}{space 3} .5918813
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} .3809473{col 26}{space 2} 1.460259{col 37}{space 1}    0.26{col 46}{space 3}0.794{col 54}{space 4}-2.481108{col 67}{space 3} 3.243003
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.190201{col 26}{space 2} 1.520077{col 37}{space 1}   -0.78{col 46}{space 3}0.434{col 54}{space 4}-4.169496{col 67}{space 3} 1.789095
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .1515821{col 26}{space 2} .2418115{col 37}{space 1}    0.63{col 46}{space 3}0.531{col 54}{space 4}-.3223598{col 67}{space 3}  .625524
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.4067721{col 26}{space 2}  .098095{col 37}{space 1}   -4.15{col 46}{space 3}0.000{col 54}{space 4}-.5990348{col 67}{space 3}-.2145095
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.888897{col 26}{space 2} 1.001321{col 37}{space 1}    1.89{col 46}{space 3}0.059{col 54}{space 4}-.0736556{col 67}{space 3} 3.851449
{txt}B__ra~_suplb {c |}{col 14}{res}{space 2}-2.274435{col 26}{space 2} .8779965{col 37}{space 1}   -2.59{col 46}{space 3}0.010{col 54}{space 4}-3.995276{col 67}{space 3}-.5535932
{txt}B__ra~nsuplb {c |}{col 14}{res}{space 2} 1.715178{col 26}{space 2} .9707347{col 37}{space 1}    1.77{col 46}{space 3}0.077{col 54}{space 4} -.187427{col 67}{space 3} 3.617783
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.475383{col 26}{space 2} .3129339{col 37}{space 1}   -4.71{col 46}{space 3}0.000{col 54}{space 4}-2.088722{col 67}{space 3}-.8620435
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1477572{col 26}{space 2} .2610123{col 37}{space 1}    0.57{col 46}{space 3}0.571{col 54}{space 4}-.3638174{col 67}{space 3} .6593318
{txt}B__politic~b {c |}{col 14}{res}{space 2}-.7108024{col 26}{space 2} .9781663{col 37}{space 1}   -0.73{col 46}{space 3}0.467{col 54}{space 4}-2.627973{col 67}{space 3} 1.206368
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2239246{col 26}{space 2}  .089147{col 37}{space 1}    2.51{col 46}{space 3}0.012{col 54}{space 4} .0491997{col 67}{space 3} .3986494
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0354943{col 26}{space 2} .0560603{col 37}{space 1}   -0.63{col 46}{space 3}0.527{col 54}{space 4}-.1453705{col 67}{space 3}  .074382
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.0040864{col 26}{space 2} .8414142{col 37}{space 1}   -0.00{col 46}{space 3}0.996{col 54}{space 4}-1.653228{col 67}{space 3} 1.645055
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-4.140369{col 26}{space 2} .7609156{col 37}{space 1}   -5.44{col 46}{space 3}0.000{col 54}{space 4}-5.631736{col 67}{space 3}-2.649002
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.230054{col 26}{space 2} .1852392{col 54}{space 4}-3.593116{col 67}{space 3}-2.866992
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1425464{col 26}{space 2} .0282021{col 54}{space 4} .0967275{col 67}{space 3} .2100692
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       880{col 27}        .{col 38}-2692.949{col 49}    29{col 58} 5443.899{col 69} 5582.517
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
. *
. *
. *
. *
. *
. *
. 
. 
. 
. **  MODEL A1.2F: RATIO OF OVER40 SUPERVISORS TO OVER40 NON-SUPERVISORS [ratio_40over_suplb; ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS [EXCLUDE VALUES OF KEY COVARIATE "ratio_40over_nonsuplb" EXCEEDING THE 1ST AND 99TH PERCENTILE VALUE]  ***
. 
. xthybrid age_discrimination ratio_40over_suplb  ratio_40over_nonsuplb   orgjustice_sem   nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 ratio_55over_totallb if ratio_40over_nonsuplb>= 0.4495327 & ratio_40over_nonsuplb<= 0.8635558 , clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio_40over_suplb  ratio_40over_nonsuplb   orgjustice_sem    nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup  ratio_minsup_nonmsup  ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       880
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       128

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}26{txt}){col 67}={res}{col 70}  1387.29
{txt}Log pseudolikelihood = {res} -2700.151{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:128} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2}-.0093691{col 26}{space 2} .0489382{col 37}{space 1}   -0.19{col 46}{space 3}0.848{col 54}{space 4}-.1052862{col 67}{space 3}  .086548
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2}-.0068764{col 26}{space 2} .0545414{col 37}{space 1}   -0.13{col 46}{space 3}0.900{col 54}{space 4}-.1137755{col 67}{space 3} .1000227
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0621307{col 26}{space 2} .0642911{col 37}{space 1}   -0.97{col 46}{space 3}0.334{col 54}{space 4}-.1881389{col 67}{space 3} .0638775
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2}-.0698526{col 26}{space 2} .0754345{col 37}{space 1}   -0.93{col 46}{space 3}0.354{col 54}{space 4}-.2177015{col 67}{space 3} .0779963
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0208913{col 26}{space 2} .0732374{col 37}{space 1}    0.29{col 46}{space 3}0.775{col 54}{space 4}-.1226515{col 67}{space 3}  .164434
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2} .0787519{col 26}{space 2} .0740647{col 37}{space 1}    1.06{col 46}{space 3}0.288{col 54}{space 4}-.0664122{col 67}{space 3} .2239161
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0253324{col 26}{space 2}  .076584{col 37}{space 1}   -0.33{col 46}{space 3}0.741{col 54}{space 4}-.1754343{col 67}{space 3} .1247694
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2} .0179696{col 26}{space 2} .0802018{col 37}{space 1}    0.22{col 46}{space 3}0.823{col 54}{space 4} -.139223{col 67}{space 3} .1751622
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}-.0041964{col 26}{space 2} .0887349{col 37}{space 1}   -0.05{col 46}{space 3}0.962{col 54}{space 4}-.1781137{col 67}{space 3} .1697209
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8401162{col 26}{space 2} .0315046{col 37}{space 1}   26.67{col 46}{space 3}0.000{col 54}{space 4} .7783683{col 67}{space 3} .9018641
{txt}W__ra~_suplb {c |}{col 14}{res}{space 2}-.1583488{col 26}{space 2} 1.149375{col 37}{space 1}   -0.14{col 46}{space 3}0.890{col 54}{space 4}-2.411083{col 67}{space 3} 2.094386
{txt}W__ra~nsuplb {c |}{col 14}{res}{space 2} .7328271{col 26}{space 2} 1.163036{col 37}{space 1}    0.63{col 46}{space 3}0.529{col 54}{space 4}-1.546682{col 67}{space 3} 3.012336
{txt}W__orgjust~m {c |}{col 14}{res}{space 2} .0402853{col 26}{space 2}  .263419{col 37}{space 1}    0.15{col 46}{space 3}0.878{col 54}{space 4}-.4760065{col 67}{space 3} .5565771
{txt}W__nonprof~b {c |}{col 14}{res}{space 2}-.1084576{col 26}{space 2} 1.514327{col 37}{space 1}   -0.07{col 46}{space 3}0.943{col 54}{space 4}-3.076483{col 67}{space 3} 2.859568
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.179761{col 26}{space 2} 1.525504{col 37}{space 1}   -0.77{col 46}{space 3}0.439{col 54}{space 4}-4.169694{col 67}{space 3} 1.810171
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .2062834{col 26}{space 2} .2374772{col 37}{space 1}    0.87{col 46}{space 3}0.385{col 54}{space 4}-.2591634{col 67}{space 3} .6717301
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.3879599{col 26}{space 2} .1057587{col 37}{space 1}   -3.67{col 46}{space 3}0.000{col 54}{space 4}-.5952432{col 67}{space 3}-.1806767
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.700942{col 26}{space 2} 1.006953{col 37}{space 1}    1.69{col 46}{space 3}0.091{col 54}{space 4}-.2726508{col 67}{space 3} 3.674534
{txt}B__ra~_suplb {c |}{col 14}{res}{space 2}-2.082777{col 26}{space 2}  .798938{col 37}{space 1}   -2.61{col 46}{space 3}0.009{col 54}{space 4}-3.648667{col 67}{space 3}-.5168876
{txt}B__ra~nsuplb {c |}{col 14}{res}{space 2} 1.954598{col 26}{space 2} .9526143{col 37}{space 1}    2.05{col 46}{space 3}0.040{col 54}{space 4} .0875083{col 67}{space 3} 3.821688
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.449969{col 26}{space 2} .3212064{col 37}{space 1}   -4.51{col 46}{space 3}0.000{col 54}{space 4}-2.079522{col 67}{space 3}-.8204159
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .2047416{col 26}{space 2} .2557592{col 37}{space 1}    0.80{col 46}{space 3}0.423{col 54}{space 4}-.2965373{col 67}{space 3} .7060204
{txt}B__politic~b {c |}{col 14}{res}{space 2}-.6597229{col 26}{space 2} .9265764{col 37}{space 1}   -0.71{col 46}{space 3}0.476{col 54}{space 4}-2.475779{col 67}{space 3} 1.156334
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2267854{col 26}{space 2} .0918976{col 37}{space 1}    2.47{col 46}{space 3}0.014{col 54}{space 4} .0466694{col 67}{space 3} .4069013
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2}-.0360942{col 26}{space 2} .0564176{col 37}{space 1}   -0.64{col 46}{space 3}0.522{col 54}{space 4}-.1466707{col 67}{space 3} .0744822
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.1680912{col 26}{space 2}  .862315{col 37}{space 1}   -0.19{col 46}{space 3}0.845{col 54}{space 4}-1.858198{col 67}{space 3} 1.522015
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} -4.44623{col 26}{space 2} .7458802{col 37}{space 1}   -5.96{col 46}{space 3}0.000{col 54}{space 4}-5.908129{col 67}{space 3}-2.984332
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.253912{col 26}{space 2}  .180207{col 54}{space 4}-3.607112{col 67}{space 3}-2.900713
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2} .1449703{col 26}{space 2} .0283099{col 54}{space 4}  .098868{col 67}{space 3} .2125702
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       880{col 27}        .{col 38}-2700.151{col 49}    29{col 58} 5458.302{col 69}  5596.92
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}.    
. 
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. ** MODEL A1.2G: DISAGGREGATE SUPERVISOR/SUBORDINATE RATIO MEASURES [RATIO OF ratio_40over_suplb TO ratio_40over_nonsuplb]: ONLY RANDOM INTERCEPT MODEL SPECIFICATION WITH BE & WE ESTIMATES FOR ALL COVARIATES [SANS YEAR UNIT EFFECTS & LN(TOTAL WORKFORCE)] --- FULL MODEL: ALL CONTROL COVARIATES ARE LNTEF & YEAR UNIT EFFECTS [EXCLUDE VALUES OF KEY COVARIATE "ratio40suplb_nonsuplb" EXCEEDING THE 1ST AND 99TH PERCENTILE VALUE] ***
. 
. xthybrid age_discrimination  ratio40suplb_nonsuplb    orgjustice_sem   nonprof40over_tr_lb     politicization_lb ratio_fsup_msup ratio_minsup_nonmsup lntwf ///
> yr2 yr3 yr4 yr5 yr6 yr7 yr8 yr9 yr10 ratio_55over_totallb if ratio40suplb_nonsuplb  >= 1.028541 &  ratio40suplb_nonsuplb  <= 1.834515, clusterid(a_id) vce(cluster a_id)  family(nbinomial) link(log) full ///
> use(ratio40suplb_nonsuplb   orgjustice_sem    nonprof40over_tr_lb    politicization_lb   ratio_fsup_msup ratio_minsup_nonmsup ratio_55over_totallb) 

{res}
{txt}{hline}
{p 0 8}Model {hi:model}{p_end}
{hline}

{txt}Mixed-effects GLM{col 49}{txt}Number of obs{col 67}={res}{col 69}       881
{txt}Family: {col 15}{res}negative binomial
{txt}Link: {col 29}{res}log
{txt}Overdispersion: {col 28}{res}mean
{txt}Group variable: {col 28}{res}a_id{col 49}{txt}Number of groups{col 67}={res}{col 69}       128

{col 49}{txt}Obs per group:
{col 63}{txt}min{col 67}={res}{col 69}         1
{col 63}{txt}avg{col 67}={res}{col 69}       6.9
{col 63}{txt}max{col 67}={res}{col 69}        10

{txt}Integration method: {col 21}{res}mvaghermite{col 49}{txt}Integration pts.{col 67}={col 78}{res}7

{col 49}{txt}Wald chi2({res}24{txt}){col 67}={res}{col 70}  1286.60
{txt}Log pseudolikelihood = {res} -2711.027{col 49}{txt}Prob > chi2{col 67}={res}{col 73}0.0000
{txt}{ralign 78:(Std. Err. adjusted for {res:128} clusters in a_id)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}age_discri~n{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}R__yr2 {c |}{col 14}{res}{space 2}-.0156336{col 26}{space 2} .0476662{col 37}{space 1}   -0.33{col 46}{space 3}0.743{col 54}{space 4}-.1090577{col 67}{space 3} .0777906
{txt}{space 6}R__yr3 {c |}{col 14}{res}{space 2}-.0209215{col 26}{space 2} .0540175{col 37}{space 1}   -0.39{col 46}{space 3}0.699{col 54}{space 4}-.1267939{col 67}{space 3}  .084951
{txt}{space 6}R__yr4 {c |}{col 14}{res}{space 2}-.0781831{col 26}{space 2}  .064086{col 37}{space 1}   -1.22{col 46}{space 3}0.222{col 54}{space 4}-.2037893{col 67}{space 3}  .047423
{txt}{space 6}R__yr5 {c |}{col 14}{res}{space 2}-.0864152{col 26}{space 2} .0763668{col 37}{space 1}   -1.13{col 46}{space 3}0.258{col 54}{space 4}-.2360914{col 67}{space 3}  .063261
{txt}{space 6}R__yr6 {c |}{col 14}{res}{space 2} .0009365{col 26}{space 2} .0710001{col 37}{space 1}    0.01{col 46}{space 3}0.989{col 54}{space 4}-.1382212{col 67}{space 3} .1400942
{txt}{space 6}R__yr7 {c |}{col 14}{res}{space 2}  .053679{col 26}{space 2} .0769497{col 37}{space 1}    0.70{col 46}{space 3}0.485{col 54}{space 4}-.0971397{col 67}{space 3} .2044977
{txt}{space 6}R__yr8 {c |}{col 14}{res}{space 2}-.0488308{col 26}{space 2} .0797896{col 37}{space 1}   -0.61{col 46}{space 3}0.541{col 54}{space 4}-.2052155{col 67}{space 3} .1075539
{txt}{space 6}R__yr9 {c |}{col 14}{res}{space 2}  .003594{col 26}{space 2} .0821517{col 37}{space 1}    0.04{col 46}{space 3}0.965{col 54}{space 4}-.1574204{col 67}{space 3} .1646083
{txt}{space 5}R__yr10 {c |}{col 14}{res}{space 2}-.0205784{col 26}{space 2} .0930224{col 37}{space 1}   -0.22{col 46}{space 3}0.825{col 54}{space 4}-.2028989{col 67}{space 3} .1617421
{txt}{space 4}R__lntwf {c |}{col 14}{res}{space 2} .8454663{col 26}{space 2} .0319187{col 37}{space 1}   26.49{col 46}{space 3}0.000{col 54}{space 4} .7829068{col 67}{space 3} .9080258
{txt}W__ratio40~b {c |}{col 14}{res}{space 2}-.2060402{col 26}{space 2} .5103184{col 37}{space 1}   -0.40{col 46}{space 3}0.686{col 54}{space 4}-1.206246{col 67}{space 3} .7941654
{txt}W__orgjust~m {c |}{col 14}{res}{space 2}  .074649{col 26}{space 2} .2580371{col 37}{space 1}    0.29{col 46}{space 3}0.772{col 54}{space 4}-.4310944{col 67}{space 3} .5803923
{txt}W__nonprof~b {c |}{col 14}{res}{space 2} .2289257{col 26}{space 2} 1.025625{col 37}{space 1}    0.22{col 46}{space 3}0.823{col 54}{space 4}-1.781262{col 67}{space 3} 2.239114
{txt}W__politic~b {c |}{col 14}{res}{space 2}-1.271286{col 26}{space 2} 1.529719{col 37}{space 1}   -0.83{col 46}{space 3}0.406{col 54}{space 4}-4.269479{col 67}{space 3} 1.726908
{txt}W__ratio_f~p {c |}{col 14}{res}{space 2} .1444112{col 26}{space 2} .2595929{col 37}{space 1}    0.56{col 46}{space 3}0.578{col 54}{space 4}-.3643816{col 67}{space 3}  .653204
{txt}W__ratio_m~p {c |}{col 14}{res}{space 2}-.3817717{col 26}{space 2} .1063387{col 37}{space 1}   -3.59{col 46}{space 3}0.000{col 54}{space 4}-.5901917{col 67}{space 3}-.1733517
{txt}W__ratio_5~b {c |}{col 14}{res}{space 2} 1.856205{col 26}{space 2} .9953402{col 37}{space 1}    1.86{col 46}{space 3}0.062{col 54}{space 4}-.0946262{col 67}{space 3} 3.807035
{txt}B__ratio40~b {c |}{col 14}{res}{space 2}-1.067841{col 26}{space 2} .5281523{col 37}{space 1}   -2.02{col 46}{space 3}0.043{col 54}{space 4}-2.103001{col 67}{space 3}-.0326815
{txt}B__orgjust~m {c |}{col 14}{res}{space 2}-1.519189{col 26}{space 2} .3216181{col 37}{space 1}   -4.72{col 46}{space 3}0.000{col 54}{space 4}-2.149549{col 67}{space 3}-.8888291
{txt}B__nonprof~b {c |}{col 14}{res}{space 2} .1585766{col 26}{space 2} .2743906{col 37}{space 1}    0.58{col 46}{space 3}0.563{col 54}{space 4}-.3792192{col 67}{space 3} .6963723
{txt}B__politic~b {c |}{col 14}{res}{space 2}-.6421355{col 26}{space 2} 1.011946{col 37}{space 1}   -0.63{col 46}{space 3}0.526{col 54}{space 4}-2.625513{col 67}{space 3} 1.341242
{txt}B__ratio_f~p {c |}{col 14}{res}{space 2} .2462621{col 26}{space 2} .0931899{col 37}{space 1}    2.64{col 46}{space 3}0.008{col 54}{space 4} .0636133{col 67}{space 3}  .428911
{txt}B__ratio_m~p {c |}{col 14}{res}{space 2} -.033321{col 26}{space 2} .0598942{col 37}{space 1}   -0.56{col 46}{space 3}0.578{col 54}{space 4}-.1507114{col 67}{space 3} .0840694
{txt}B__ratio_5~b {c |}{col 14}{res}{space 2}-.4454368{col 26}{space 2} .7324444{col 37}{space 1}   -0.61{col 46}{space 3}0.543{col 54}{space 4}-1.881001{col 67}{space 3} .9901279
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-3.495922{col 26}{space 2} 1.029224{col 37}{space 1}   -3.40{col 46}{space 3}0.001{col 54}{space 4}-5.513163{col 67}{space 3}-1.478681
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}/lnalpha {c |}{col 14}{res}{space 2}-3.239979{col 26}{space 2} .1772605{col 54}{space 4}-3.587404{col 67}{space 3}-2.892555
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}a_id        {col 14}{txt}{c |}
   var(_cons){c |}{col 14}{res}{space 2}  .152524{col 26}{space 2} .0296261{col 54}{space 4} .1042321{col 67}{space 3} .2231901
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:{stata estimates replay model:model}}{col 14}{c |}{res}{col 16}       881{col 27}        .{col 38}-2711.027{col 49}    27{col 58} 5476.054{col 69} 5605.143
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. *
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      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jp18390\Dropbox\DISCRIMINATION PROJECT (U.S. FEDERAL AGENCIES)\Age Discrimination Project\PAR R&R\Statistics\Age_Discrimination.APPENDIX 1.MISC SENSITIVITY CHECKS.06-02-2022.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 2 Jun 2022, 18:05:55
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